Study Protocol for the Peruvian Registry of Advanced Heart Failure (REPICAV)

Chacón-Diaz M.; Laymito Quispe R.; Hernández-Vásquez A.; Vargas-Fernández R. · Frontiers in Cardiovascular Medicine (2022) · DOI: 10.3389/fcvm.2022.896821

Resumen

Background: Heart failure (HF) is a global problem with a high mortality rate, and advanced HF (AHF) represents the stage with the highest morbidity and mortality. We have no local data on this population and its treatment. The aim of this study will be to determine the epidemiological, clinical, therapeutic, and annual survival characteristics of patients diagnosed with AHF treated in hospitals with HF units in the city of Lima, Peru. Methods and Analysis: An observational, prospective, multicenter study will be conducted with evaluation at baseline and follow-up at 1, 3, 6, and 12 months after study entry. Patients over 18 years of age with AHF seen in referral health facilities in metropolitan Lima will be included. The cumulative mortality during follow-up will be estimated by the Kaplan-Meier method, and Cox regression models will calculate hazard ratios (HRs) and 95% confidence intervals (CI). Likewise, risk ratio (RR) and 95% CI will be estimated using generalized linear models with binomial family and log link function. This study was approved by the Ethics and Research Committee of the National Cardiovascular Institute (Instituto Nacional Cardiovascular “Carlos Alberto Peschiera Carrillo”—INCOR [in Spanish]; Approval report 46/2021-CEI). Discussion: In Peru, there are no scientific data on the epidemiology of AHF in the population. This means that physicians are not adequately trained in the characteristics of the Peruvian population to identify patients who could be candidates for advanced therapies and to recognize the optimal time to refer these patients to more complex HF units. This study will be the first to examine the clinical-epidemiological characteristics of AHF in Peru with a follow-up of 1 year after the event and will provide relevant information on these observable characteristics for the management of high-complexity patients. Copyright

Instituciones: Universidad Científica del Sur; Universidad San Ignacio de Loyola